Nature communicationsApr 17, 2026

Mouth bacteria patterns linked to biological age and health

Longevity & Aging Weekly Brief ↗PubMed ↗DOI ↗OA ↗

Updated Jun 27, 2026

Abstract

Essence

An oral microbiome aging score predicted biological age and was associated with mortality, frailty, kidney function, and added disease-risk prediction.

Evidence

This observational machine-learning analysis used oral microbiome data from two NHANES cohorts (N = 4,675) and an external cohort (N = 1,293), identifying 64 age-dependent genera and testing the OMAA residual score against health outcomes.

Caveat

The health links come from cohort associations, and the abstract does not establish causality or clinical benefit from using the biomarker.

Simplified

Identifying robust, non-invasive biomarkers of biological age is key to preventive medicine. While gut aging clocks exist, the oral microbiome remains underexplored as a quantitative biomarker. Using oral microbiome data from two NHANES cohorts (N = 4,675), we identified 64 age-dependent bacterial genera and developed a machine learning model predicting chronological age, with generalizability in an independent external cohort (N = 1,293). We derived an Oral Microbiome Aging Acceleration (OMAA) Score as the residual of predicted age against chronological age. The OMAA Score independently predicted all-cause mortality (HR = 1.05, P = 0.024) and frailty (OR = 1.05, P = 0.008), correlated with impaired kidney function (lower eGFR: β = -0.066, P = 5.22×10), and enhanced risk prediction for cancer (AUC 0.70 vs. 0.67, P = 0.009) and heart attack (AUC 0.79 vs. 0.76, P = 0.016) beyond conventional risk factors. Diet and medication had minimal association. The OMAA Score offers a scalable, non-invasive tool to identify high-risk individuals for age-related morbidity and mortality. -4